In these lectures, Prof. Patrick Winston introduces the 6.034 material from a conceptual, big-picture perspective. Topics include reasoning, search, constraints, learning, representations, architectures, and probabilistic inference.
– May 9, 2019
Excellent class. Prof Patrick Winston is a great teacher. I loved how he went into the history of how AI developed and got deep into the math.
The class is far towards the theory heavy side than the practical side, so some students might not like this.
Also, this is a more general AI class, and I was mostly only interested in neural nets initially, but I actually ended up taking most of the other lectures as well.
– May 9, 2019
I thought this was one of the best courses in the major at MIT.
It was a survey of major methods in AI with some coverage of success cases. I liked the programming assignments, which were in LISP. It gave me a good foundation for later work in robotics and AI.
Back in the day they had a bit of a bias (no pun intended) against neural networks. I thought that was a weakness. Neural nets turned out to be the most important method I used in my later work. Not sure if they have revised the curriculum.
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